Question

我有两个不同长度的数据框，一个关于人口，另一个关于死亡。我需要合并它们。这是人口表的结构......

Year     Age      Female         Male        Total
1933       0     984472.26   1015361.55   1999833.81
1933       1    1040496.02   1064088.29   2104584.31
1933       2    1093043.81   1117527.14   2210570.95
1933       3    1107994.31   1135046.59   2243040.90
1933       4    1130624.43   1179513.62   2310138.05
1933       5    1168930.56   1228225.14   2397155.70
1933       6    1190706.56   1238800.33   2429506.89
1933       7    1203816.58   1245575.51   2449392.09
1933       8    1224285.20   1255721.28   2480006.48
1933       9    1230968.73   1254639.67   2485608.40
1933      10    1243608.10   1262739.94   2506348.04

死亡表的结构与人口相同但具有不同的值。如果您注意到每行的年龄增量。填充表的行数多于死亡表。在合并两个表之后，我希望在死亡行中有NaN's。但是，在运行代码以合并表之后，我得到以下输出...

  year,p_age,p_female,p_male,p_total,d_age,d_female,d_male,d_total
0,1933,0,984472.26,1015361.55,1999833.81,0,52615.77,68438.11,121053.88
1,1933,0,984472.26,1015361.55,1999833.81,1,8917.13,10329.16,19246.29
2,1933,0,984472.26,1015361.55,1999833.81,2,4336.92,5140.05,9476.97
3,1933,0,984472.26,1015361.55,1999833.81,3,3161.59,3759.88,6921.47
4,1933,0,984472.26,1015361.55,1999833.81,4,2493.84,2932.59,5426.43
5,1933,0,984472.26,1015361.55,1999833.81,5,2139.87,2537.53,4677.4
6,1933,0,984472.26,1015361.55,1999833.81,6,1939.7,2337.76,4277.46
7,1933,0,984472.26,1015361.55,1999833.81,7,1760.47,2163.9,3924.37
8,1933,0,984472.26,1015361.55,1999833.81,8,1602.2,2015.97,3618.17
9,1933,0,984472.26,1015361.55,1999833.81,9,1464.88,1893.96,3358.84
10,1933,0,984472.26,1015361.55,1999833.81,10,1357.91,1805.52,3163.43

如果您注意到年龄正在重复，数据框架从9千加上增加到100万。这是合并代码我利用......

df_usa = usa_population.merge(usa_death, how='left', on='year')

我也用过......

df_usa = pd.merge(usa_population, usa_death, how='left', on='year')

...或

df_usa = pd.merge(usa_population, usa_death, how='inner', on='year')

如何修复此代码？

Answer 1

您似乎也希望在age列上进行合并。试试这个：

df_usa = usa_population.merge(usa_death, how='left', on=['year','age'])

Pandas合并两个不同长度的数据帧

1 个答案: